TidyTuesday Week 05 Commentary

[nicoleloeb]

Code/Tools We Have Used In Class:

• RMarkdown (example)
• Importing the Tidyverse package (obviously!) and the here and janitor packages
• Using :: to specify what package to use for a function (example: readr::read_csv())
• clean_names()
• Lines 16-21 of this script are very similar to examples we've gone through in class and our homework this week using:
  • clean_names() %>% group_by() %>% filter() %>% mutate()
• pivot_longer()

Code/Tools I Want To Learn:

• I look forward to learning more about using ggplot
• Plot annotation - there are a lot of cool plots that look like infographics!
• Animated plots (example here)

Visualizations:

Plots I liked:

• Plot by Marius Grabow: just a simple area plot (or line graph with a different colour above/below the line) showing the global production of seafood over time, but they used colours to make it look like water and a beach, with a little fisherman pulling on the line. While there isn't a ton of information, the graphic grabs your attention and is easily understood.
• Plot by Jamie Hudson: similar to the plot by Marius Grabow, but showing the increasing fraction of fish stocks that are overexploited. Again, it's simple and attention grabbing!
• Plot by Dr Nicci Potts: a radial bar graph showing the percent of fish stocks that are overexploited for different seas/regions in 2015 and 2017. I think this plot really makes it easy to see what areas of the world are overexploiting the highest amount of their fish stocks, and also how different regions have made changes (for the better or worse) in a short period.

Plots that can be improved:

• Plot by Mitsuo Shiota: I think that the line plot they used for showing the share of seafood production from four of the major producing countries over time is not very effective. This could be shown better using a stacked bar graph, or an area plot like their first plot.
• Plot by Dominic: The little ships and fish added to the plot are cute, but it is difficult to interpret this line plot. The use of different line styles to represent countries and colours to represent different production types is a little confusing, particularly because they used dashed and dotted lines, and dash-dot lines, which makes it difficult to see which is which. Here, they could have used two separate axes to show the two different production types, then use colours to show the countries. This would also help show differences in the aquaculture lines, because the y-axis could be fitted to the values (which are much lower than those for capture).

[kazmiruz]

Very good analysis, Nicole! I like how you reviewed a few different types of plots and provided a short summary for each one.